Being able to detect occupancy within a monitored space, such as a room, is a common feature of multiple tasks, from lighting control to energy optimization to security monitoring, among others. Current occupancy-detection technologies present multiple disadvantages with respect to their ability to reliably detect when a room or other space is occupied by one or more people and/or animals.
Conventional occupancy-detection is typically performed using any one or more of a variety of sensors. There are a multitude of sensors that can be used to detect occupancy, including passive infrared (PIR) sensors, ultrasonic sensors, thermal imaging cameras, and visible-light cameras. Each of these sensors has certain disadvantages. A PIR sensor, for example, is reliable for detecting movement, but if a person is in a space and does not move for some period, then the PIR sensor will not be able to detect that person's presence. Due to this disadvantage, PIR sensors are typically used in conjunction with timers to keep a space lit in lighting control applications. Ultrasonic sensors have similar performance to PIR sensors, but their range is longer, they have a larger form factor, require more energy to operate, and are more expensive. Thermal imagers solve the issue presented by PIR sensors for detecting occupancy with an immobile person, but they have the disadvantages of being more expensive and complicated to use. In addition, thermal imagers' performance is affected by background thermal changes, which can trigger false-positive occupancy detection. For example, if a window (a high heat transfer element) is within the coverage area of the sensor, the window's thermal profile can trigger the sensor. Video cameras can be a very reliable way to detect occupancy, but they require large computational infrastructure and direct line of sight for the image processing needed to recognize human and/or animal forms. In addition, video cameras raise privacy concerns, such as when using them in bathrooms or other areas where privacy is expected.